Hi, AgitatedDove14

How do I set the version to 1.5.1,? When I launch the autoscaler the version 1.5.0 is picked by default.

Yes the example works. As the example, in my code I am basically starting with doing, was not that supposed to work?

` @hydra.main(config_path="config", config_name="config")
def main(cfg: DictConfig):

import os
import pytorch_lightning as pl
import torch
import yaml
import clearml

pl.seed_everything(cfg.seed)

task = clearml.Task.init(
    project_name=cfg.project_name,
    task_name=cfg.task_name,
) `

Great. Thank you.

I have a task that is already completed, and, in other script, I am trying to load it and analyse the results.

I think not, I have not set any ENV variable. Just went to the web UI, added an autoscaler, filled the data in the UI and launched the autoscaler.

By inspecting the scaler task, it is running the following docker image: allegroai/clearml-agent-services-app:app-1.1.1-47

With the account admin email. The one in which I got the receipt.

I am launching through the UI, "XXX workspace / https://app.clear.ml/applications / AWS Autoscaler".

So It could be launched by the clearml cli? I can also try that.

I do not recall the older version, It is from a couple of months ago, but the new version is WebApp: 1.2.0-153 • Server: 1.2.0-153 • API: 2.16

Thank you, After running the script, I run docker-compose -f /opt/clearml/docker-compose.yml up -d ?

Thank you, it is working now.

Hi, sorry for the delay. rmdatasets == 0.0.1 is the name of the local package that lives in the same repo as the training code. Instead of picking the relative path to the package.

As as work around I set the setting to force the use of requirements.txt and I am using this script to generate it:

` import os
import subprocess

output = subprocess.check_output(["pip", "freeze"]).decode()

with open("requirements.txt", "w") as f:
for line in output.split("\n"):
if " @" in line...

I am using hydra to configure my experiments. Specifically, I want to retrieve the OmegaConf data created by hydra, config = task.get_configuration_objects() returns a string with those values, but I do not know how to parse it, or whether I can get this data in a nested dict.

Hydra params are still not upload on 1.0.4

SuccessfulKoala55 , how do I set the agent version when creating the autoscaler?

Actually, this error happens when a launch the autoscaler from the Web UI, when I enqueue a task, it launches an EC2 instance which "Status Check" stays in "Pending" for over 15 minutes and then the instance is terminated by the scaler that launches another one in a loop.

Yes, but the issue is caused because rmdatasets is installed in the local environments, I needed it installed in order to test the code locally, so it is caught on the package list.
I will probably stop installing the sibling packages and adding them manually to sys.path.

Basically, I am following the steps in this video:
https://www.youtube.com/watch?v=j4XVMAaUt3E

AgitatedDove14 , here follows the full log:

Follows the failure part of the log:
` Requirement already satisfied: pip in /root/.clearml/venvs-builds/3.1/lib/python3.10/site-packages (22.2.2)
Collecting Cython
Using cached Cython-0.29.32-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (1.9 MB)
Installing collected packages: Cython
Successfully installed Cython-0.29.32
Collecting boto3==1.24.59
Using cached boto3-1.24.59-py3-none-any.whl (132 kB)
ERROR: Could not find a version that satisfies the requ...

Hi, any update on that?

Thank you, sorry for the daly, I have been playing around with this setup, right now I am generating a requirements.txt with git links to the sibling packages, I had to set on the agent to force the use of the reuqirements.txt. But I am starting to wonder whether It would be easier just changing sys,path on the scripts that use the sibling libs.

Thank you for your response, so what is the difference between sync and add? By your description it seems to make no difference whether I added the files via sync or add, since I will have to create a new dataset either way.

Let's see if I got how it works on the CLI.
So if I execute:
clearml-data create --name <improved_dataset> --parents <existing_dataset_id>
Where the parent dataset was updated with sync,
I just need to run:
clearml-data upload --id <created_dataset_id>
And the delta will be automatically uploaded to the new dataset?

They are on the same repo on git, something like:
my-repo train project1 project2 libs lib1 ...

Solved by removing default parts.

Now I got a strange behavior in which I have 2 tasks on queue, the autoscaler fires two EC2 instances and then turn them off without running the tasks, then It fires two new instances again in a loop.

Thanks, I thought on doing that, but I was wondering if there was a way to set it into the code.

Thank you, I was importing everything inside the function so the the hydra autocomplete would run faster.

I used the autogenerated clearml.conf, I will try erasing the unnecessary parts.

So I guess I am referring to the auto package detection. I am running the job though the web ui. My actual problem is that I have a private repo on my requirements.txt (listed with the github url) that is not being installed. Also, my environment.yaml uses python 3.8, while 3.9 is being installed.